Bekolay Trevor, Stewart Terrence C, Eliasmith Chris
Centre for Theoretical Neuroscience, University of Waterloo Waterloo, ON, Canada.
Front Neurosci. 2015 Oct 19;9:380. doi: 10.3389/fnins.2015.00380. eCollection 2015.
Nengo is a software package for designing and simulating large-scale neural models. Nengo is architected such that the same Nengo model can be simulated on any of several Nengo backends with few to no modifications. Backends translate a model to specific platforms, which include GPUs and neuromorphic hardware. Nengo also contains a large test suite that can be run with any backend and focuses primarily on functional performance. We propose that Nengo's large test suite can be used to benchmark neuromorphic hardware's functional performance and simulation speed in an efficient, unbiased, and future-proof manner. We implement four benchmark models and show that Nengo can collect metrics across five different backends that identify situations in which some backends perform more accurately or quickly.
Nengo是一个用于设计和模拟大规模神经模型的软件包。Nengo的架构设计使得同一个Nengo模型几乎无需修改就能在多个Nengo后端中的任何一个上进行模拟。后端将模型转换为特定平台，其中包括GPU和神经形态硬件。Nengo还包含一个大型测试套件，该套件可以与任何后端一起运行，并且主要关注功能性能。我们建议，可以使用Nengo的大型测试套件以高效、无偏见且面向未来的方式对神经形态硬件的功能性能和模拟速度进行基准测试。我们实现了四个基准模型，并表明Nengo可以跨五个不同后端收集指标，这些指标能识别出某些后端在哪些情况下表现得更准确或更快。
